Bipolar Queries Research Articles

A novel approach to hierarchical contextual bipolar queries: A winnow operator approach

Abstract We propose a new approach to the bipolar database queries, which involve a necessary (required) and optional (desired) conditions, connected with a non-conventional aggregation operator “and possibly”, combined with a context, exemplified by “find houses which are cheap and – with respect to other houses in town – possibly close to a railroad station”. We use our winnow operator based interpretation of the bipolar queries. We assume that the query, posed by the human user, involves terms, which do not directly relate to attributes, and which are then to be decoded using a concept of a query hierarchy, leading to the queries, which involve terms directly related to attribute values. The original query is considered to be of level 0, at the bottom of the precisiation hierarchy, then its required and optional parts are assumed to be bipolar queries themselves, both accounting for context. The precisiation proceeds further, to level 1 queries, level 2, etc. A real estate related example is provided as illustration.

Fuzziness in database management systems: Half a century of developments and future prospects

This comprehensive, bird's view research note combines the state of the art, a brief presentation of the history and some original solutions, and position like views of some prospective future developments of one of the most relevant and interesting areas related to the use of fuzzy logic in database management systems, notably in its querying component, and – to some extent – in a broader issue of data and information management. We briefly summarize the roots of those new applications of fuzzy logic, more relevant proposals and development in the context of fuzzification of the basic relational database model, and then some of its further generalizations. We particularly focus on fuzzy querying as a human consistent and friendly way of retrieving information due to real human intentions and preferences expressed in natural language represented via fuzzy logic and possibility theory. We mention some extensions, notably fuzzy queries with linguistic quantifiers, and point their close relation to linguistic summaries. As for newer, prospective developments, we mainly focus on bipolar queries that can accomodate the users' intentions and preferences involving some sort of a required and desired, mandatory and optional, etc. conditions. We show various ways of handling such queries. We conclude with some brief position statements of our view on relevant and promising directions, and challenges.

Bipolar queries on fuzzy univalued and multivalued attributes in object databases

Flexible querying has been developed with the aim of proposing powerful and user-friendly ways of setting and solving queries. Within the context of flexible querying, the use of bipolar queries has deserved the attention of the research community as a way of distinguishing in queries negative and positive assessments of data. Bipolar queries have been specially studied in the framework of crisp relational databases. In this paper, we propose an approach to bipolar queries in fuzzy object databases. Through the use of a generalized inclusion concept, we deal with bipolar conditions on both fuzzy univalued and multivalued attributes. The consistence of the proposed approach with the bipolar queries rationale is also analyzed.

A Fuzzy Ontology for Database Querying with Bipolar Preferences

The expression and the evaluation of complex user preferences in the context of distributed and heterogeneous information systems are tackled in this paper. Complex preferences are modeled by fuzzy bipolar conditions, which associate negative and positive conditions. Queries involving such conditions are called bipolar queries. In our case, such queries are addressed to information systems such as Web applications, built on several distributed and heterogeneous databases. This querying can lead to process huge volumes of data and can deliver massive responses, in which it is difficult to the user to distinguish the relevant answers from irrelevant ones. Semantic aspects make it possible to address this problem by providing a personalized data access method, so that only the most relevant data are targeted to evaluate queries. We introduce then in this paper a new approach for flexible querying of complex information systems that combines a reasoning mechanism (an ontology-based on the fuzzy bipolar DLR-Lite) with a bipolar relational language of a high expressivity (Bipolar SQLf language). The reasoning mechanism can also answer queries in approximative way, based on degrees expressing at which extent it is possible to substitute a concept in the query with other concepts, while still meaningful to the user.

Bipolar queries: An aggregation operator focused perspective

The concept of a bipolar query, meant as a database query that involves both negative and positive conditions, is discussed from the point of view of flexible database querying and modeling of more sophisticated intentions and preferences of the user. The aggregation of matching degrees against the negative and positive conditions to derive an overall matching degree is considered taking into account as the point of departure the Lacroix and Lavency's (1987) [1] approach and the semantics of these conditions. Three variants of formalization of the “and possibly” operator which governs the adopted aggregation mode of the negative and positive parts of a bipolar query are proposed. These variants take the form of logical formulas whose logical connectives may be modeled using fuzzy logic in many different ways. New recommendations as to the choice of such variants and sets of logical connectives, which preserve the assumed semantics of the “and possibly” operator, expressed as a number of postulated plausible, or desired, properties of aggregation, are formulated.

Bipolar database querying using bipolar satisfaction degrees

When expressing their information needs in a (database) query, users sometimes prefer to state what has to be rejected rather than what has to be accepted. In general, what has to be rejected is not necessarily the complement of what has to be accepted. This phenomenon is commonly known as the heterogeneous bipolar nature of expressing information needs. Satisfaction degrees in regular fuzzy querying approaches are based on the “symmetric'' assumption that the extent to which a database record, respectively, satisfies and does not satisfy a given query are complements of each other and are therefore less suited to adequately handle heterogeneous bipolarity in query specifications and query processing. In this paper, we present a bipolar query satisfaction modeling framework which is based on pairs that consist of an independent degree of satisfaction and degree of dissatisfaction. The use and advantages of the framework are illustrated in the context of fuzzy query evaluation in regular relational databases. More specifically, the evaluation of heterogeneous bipolar queries that contain both positive, negative, and bipolar criteria is studied. © 2011 Wiley Periodicals, Inc.

Bipolar queries in textual information retrieval: A new perspective

A new concept of a bipolar query against collections of textual documents, i.e. in the context of information retrieval (IR), is introduced using recent developments in bipolar information modeling and bipolar database queries. Specifically, a particular approach to bipolar queries with an explicit “and possibly” type of an aggregation operator is used. An effective and efficient processing of such bipolar queries using standard IR data structures is briefly discussed. The bipolar queries proposed combine a flexibility provided by fuzzy logic with a more sophisticated representation of user preferences and intentions. This combination can make the search of vast resources of textual document, notably those available via the Internet, more intelligent.

A flexible bipolar querying approach with imprecise data and guaranteed results

In this paper, we propose an approach to query a database when the user preferences are bipolar (i.e., express both constraints and wishes about the desired result) and the data stored in the database are imprecise. Results are then completely ordered with respect to these bipolar preferences, giving priority to constraints over wishes. Additionally, we propose a treatment that allows us to guarantee that any query will return a result, even if no element satisfies all constraints specified by the user. Such a treatment may be useful when user's constraints are unrealistic (i.e., cannot be all satisfied simultaneously) and when the user desires a guaranteed result. The approach is illustrated on a real-world problem concerning the selection of optimal packaging for fresh fruits and vegetables.